Video providers seek to provide the clearest possible signal to an end user. While the clearest signal would be one that is sent from a nearby originating source directly to, an individual user, it is cost prohibitive to send signals in such a manner. Television signals are generally sent from a satellite to a cable television headend, or they may originate from digital files stored by a video server at the headend. The signal is then merged with locally generated content and advertising for distribution. In order to maximize available resources, signals are multiplexed so that multiple signals can be sent over a single communication channel. The multiplexed signal is received by an imaging device such as a set top box, demultiplexed and decoded and then sent to a video display device such as a television or computer screen. During this process, the video quality can degrade at one or more points resulting in an image that is not satisfactory for the viewer. While the quality of the video image can be instantly evaluated by human viewers, subjective testing is time consuming and is not useful for operational monitoring, line testing, or other types of periodic or continual monitoring and testing that are required to ensure the fidelity of a transmission. Subjective testing also varies according to the user's point of view.
Automated image evaluation systems compare the transmitted and/or decoded signals to a template or other “golden” standard signal. Such systems measure things like the Peak Signal to Noise Ratio (PSNR) using metrics such as Mean Squared Error calculations (MSE). Typical values for the PSNR in lossy image and video compression are between 30 and 50 dB, where higher is better. Acceptable values for wireless transmission quality loss are considered to be about 20 dB to 25 dB. However, PSNR does not always rank quality of an image or video sequence in the same way that a person would. Furthermore, the original video or template is generally not available at an arbitrary place for evaluation.
There is therefore a need in the art for an automated means of identifying degradation in a video image without requiring comparison to a reference image.